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Found 10 papers, 1 papers with code
SB_NITK at MEDIQA 2021: Leveraging Transfer Learning for Question Summarization in Medical Domain
Recent strides in the healthcare domain, have resulted in vast quantities of streaming data available for use for building intelligent knowledge-based applications.
HaleLab_NITK@SMM4H’22: Adaptive Learning Model for Effective Detection, Extraction and Normalization of Adverse Drug Events from Social Media Data
This paper describes the techniques designed for detecting, extracting and normalizing adverse events from social data as part of the submission for the Shared task, Task 1-SMM4H’22.
Ensemble ALBERT and RoBERTa for Span Prediction in Question Answering
Retrieving relevant answers from heterogeneous data formats, for given for questions, is a challenging problem.
Improving Clinical Diagnosis Performance with Automated X-ray Scan Quality Enhancement Algorithms
In clinical diagnosis, diagnostic images that are obtained from the scanning devices serve as preliminary evidence for further investigation in the process of delivering quality healthcare.
A Bag of Visual Words Model for Medical Image Retrieval
Medical Image Retrieval is a challenging field in Visual information retrieval, due to the multi-dimensional and multi-modal context of the underlying content.
Leveraging Multimodal Behavioral Analytics for Automated Job Interview Performance Assessment and Feedback
Such analysis is then used to provide constructive feedback to the interviewee for their behavioral cues and body language.
Hybrid Text Feature Modeling for Disease Group Prediction using Unstructured Physician Notes
Such unstructured clinical notes recorded by medical personnel can also be a potential source of rich patient-specific information which can be leveraged to build CDSSs, even for hospitals in developing countries.
Coherence-based Modeling of Clinical Concepts Inferred from Heterogeneous Clinical Notes for ICU Patient Risk Stratification
In hospitals, critical care patients are often susceptible to various complications that adversely affect their morbidity and mortality.
Proximal Policy Optimization for Improved Convergence in IRGAN
IRGAN is an information retrieval (IR) modeling approach that uses a theoretical minimax game between a generative and a discriminative model to iteratively optimize both of them, hence unifying the generative and discriminative approaches.
ARS\_NITK at MEDIQA 2019:Analysing Various Methods for Natural Language Inference, Recognising Question Entailment and Medical Question Answering System
In this paper, we present three approaches for Natural Language Inference, Question Entailment Recognition and Question-Answering to improve domain-specific Information Retrieval.
